I have a need for a series of blog posts for my new project. I narrowed down 5 options 1/ ChatGPT – paid or free, 2/ Jasper.AI – a specialized content writing platform priced at $49 per month, 3/ Bard – free, 4/ Bing Chat – free and 5/ Using a writer on Fiverr.

I stated with writing only 1 blog post and tried the approach of using the “same prompt” for all the generative AI solutions and mostly the same brief for my Fiverrr gig.

Create a 1500 word blog post on “review of courses on options trading ” using this URL –

https://www.investopedia.com/best-options-trading-courses-5120500

as a starting point

TLDR: If you are seriously interested in using these and other solutions, I dont think the game is using one versus another. I used all of them and they each gave me different things to make the blog post better.

The first was Google Bard.

While I was expecting it to be not a great experience, it surprised me with a concise article, with relevant facts and a good summary. It did not, however give me 1500 words. It came closer to 500-600 words.

Next I used ChatGPT.

It did a good job with some generic writing, which I had to tweak, but its content was different from Google Bard. It tended to be more generic writing however, so I had to rewrite quite a bit. I used it more for the framework and for checking the overall structure.

Next was Bing Chat – which refused to write a blog post, saying it was not capable to do so. Instead I had to give a different prompt “Summarize the page for me and give me 3 pages like this, and summarize those too”.

Since Jasper.ai offers a 10,000 word free trial, I tried, that too. Of the lot it is the best for “writers”. But if you want it to generate a lot of content, I am not convinced yet that the $49 per month is worth it. It is very good if content is your job, but for someone like me the “free and good enough” options were way more useful.

Finally I tried giving the brief to “Fiverr“. 1 day later, I am still getting responses and bids.

Goodbye Fiverr.

Check out Options Trading Course and Review of Options trading to see the final output.

The good thing about Generative is that its writes for you. It can create content with simple prompts. For example, I created an AI image with the “prompt” – Artificial Intelligence Enabled Chat Conversations in StarryAI.

But for good quality content (as opposed to the base, standard nonsense it usually spits out), you need to coax it with a very descriptive prompt.

I am not sure why it generated this image. It has nothing to do with my prompt as you can see.

Turns out you have to speak to it in not “human language”, but using a specific set of keywords which is the prompt syntax.

On Night Cafe, I used the same prompt and got this.

Again, I am not sure what this is either – It is not “Artificial Intelligence Enabled Chat Conversations” in my mind.

That’s why “Prompt Engineering” is a thing and companies are paying $350K a year for those jobs.

Substack, the email newsletter subscription business, today announced it will allow its writers and creators to invest in its startup starting at $100 and increments thereof.

Substack is looking to raise $2 Million at a pre money valuation of $585 Million.

They have 2 million paid subscribers, and 35 million subscribers, allowing for $300M to be paid to writers (their goal is writers keep 86% of the money earned from subscriptions).

You do not have to be an accredited investor (have over $1 Million in liquid assets) to invest in the round, and can invest at least $2200 or even start at $1000.

I think the valuation at $585M is rich, relatively speaking but I dont know all the numbers.

Here are some assumptions based on the data provided:

1. They are probably doing $150M to $200M in overall revenue given they have paid $300M overall to writers and have 2M paid subscribers. At an average of $7 per month per subscriber, it rounds up to $168M LTM (Last Twelve Months).
2. Their take is 10% or about $15M to $20M, which is their “actual revenue).
3. The growth rate seems tremendous, which I am assuming is over 100% YoY given 2 years ago they had only 100K paying subscribers.
4. So $20M in revenue, growing at over 100% YoY and you are paying 25X to 30X in Market Cap to Sales – Very rich, but this is the private market. They still are probably stuck in 2021 valuations.

The basic assumption I make when I form an opinion about new things (technologies, processes, startups, etc.) is that my opinion will have to change over time.

As the amount of knowledge one has increases, the first opinion becomes less relevant.

The last weekend I participated in hackathon at Surf Incubator. The focus of the hackathon was AI, or more in particular OpenAI APIs. Every team had 3-5 hours to hack a new AI app.

The one I chose to build was FashionGPT, which would take your selfie or photo and give you 3-5 options on how you would look with the latest fashion outfits from luxury brands such as Gucci, Giorgio Armani, etc.

It is a virtual trial room. You dont need to try new outfits, just see what you’d look like so you can share on Social media and get feedback before you decide to buy.

I worked with one other person, who quickly gave up and I complete the 3 modules – Javascript + HTML front end, Python at the back with Django on AWS. I pushed it to Github.

All the version 1 did was take your photo, then I asked ChatGPT for names of 100 top luxury brands, 100 top colors and 100 top outfits styles in 4 seasons (Fall, Winter, Spring, Summer).

The “prompt” to ChatGPT was a random combination of brand + color + outfit, using the create image endpoint, and then variations endpoint for 3 different colors and styles.

Until yesterday I had a very poor impression of the term “prompt engineer”. I thought that was a BS job. Since there’s no specialized “google searcher” role, why do you need a “prompt engineer”.

Turns out teasing information from LLM is a lot harder when you are not expressive. Most people are not.

I spend nearly 1 hour trying to build a random prompt base so the model could give meaningful new images from the existing set of images plus the “secret sauce” – the prompt.

“Prompt engineer” is a thing. I was wrong.

When you have a “Word document”, narrative style report – whether it is a PR/FAQ or a requirements document or any other:

1. There is a tendency to automatically “Email” the document for sharing, comment, feedback, etc. That is the first sign of trouble.

The document now becomes unwieldy. Comments, overwrites, tracking changes, etc.

2. There is a need to create a visual from a lot of writing. Which means some variables in the document (e.g. dates of multiple releases) need to be parameterized.

The document now requires manual visual creation. Also a pain.

3. There is a need to convert the “document” to a presentation for sharing with larger audiences.

The content now needs rework in a new (presentation) format.

Which is why I have now given up writing on Office 365 and instead moved all the documents to Google Docs style shared writing or Notion style Wiki (or will use Microsoft Loop)

I am going to write a series of posts on AI and in particular Generative AI. My focus is going to not be on the technology, but more the impact on specific jobs / roles.

Some assumptions I am making:

1. The generative AI genie won’t get put back into the bottle – meaning Governments cannot “regulate” companies to stop work on AI
2. There will be a host of winners and losers from this move to Generative AI – within each role and type of person.
3. While AI “evens the playing field for the “mediocre person” and the “good person”, the gap between the “great person” for a role and the others will only get larger with AI.
4. Most roles will change dramatically, not be completely eliminated. Unfortunately, instead of a company needing 10 product managers, they might be able to achieve more with fewer (5 or even less)
5. A small number of people (< 5% of the 1B on LinkedIn are active monthly users) are already using Generative AI in some form (ChatGPT, Jasper.ai) in their work already.

I am going to start with the Product Manager (PM). Specifically the technology software product manager. Not a Director or a Vice President, but just an individual contributor in a software company.

Most PMs (should) do 5 things well.

1. Assess customer needs and determine how problems customer’s have get translated into requirements
2. Prioritize what gets built by engineering / technology teams
3. Price, Position and frame the product – enabling marketing and sales teams to promote and sell
4. Collect customer feedback, track competitive landscape & measure profitability & market share
5. Train sales & support teams on product and resolve issues to incorporate into future product roadmap.

While the top 5 sounds very strategic and important, the day to day is filled with drudgery of joining tables, making queries on multiple databases, Excel wrangling, Document writing, rewriting and rewrite the rewrite.

Created with MidJourney: a man with the drudgery of working with Excel, multiple queries, doing lots of data analysis

With almost every product that a PM uses daily – including Microsoft Office, Salesforce, HubSpot, Atlassian, etc. all announcing Generative AI in their products, the “drudgery” should go away, making most PM more productive.

Which leads to fewer PM. While AI might not “eliminate” jobs, it will still displace many junior PMs.

So how can you future proof yourself?

1. Index on customer interactions, building customer trust and traction more than ever.
2. Aggressively use as much Generative AI in all you do with the intent to be more productive.
3. Research and keep up with trends and technologies outside your core functional PM job